Photosynthetic Reaction Centres Assembled on a Gold Electrode and the Photocurrent - Potential Response
Bibliographic record
Abstract
The photosynthetic reaction centre (RC) from Rhodobacter sphaeroides has been studied for use in biohybrid solar cells. Much of the previous work has focussed on improving photocurrent generation by loading the electrode surface with many copies of the protein resulting in multilayers. The primary disadvantage with this approach is the random orientation of proteins, with some supposedly oriented properly. We used RCs with Cys for covalent attachment to a gold electrode and for proper orientation. Areas of bare electrode surface and RCs bound non-specifically (i.e. not bound via the Cys) were competitively displaced by an insulating, non-redox layer of mercaptohexanol (MCH). The adsorbed monolayer of RCs was imaged using atomic force microscopy to detail the distribution of RCs on the gold surface for surfaces prepared with different RC deposition concentrations. Photocurrents were measured for all RC modified surfaces using a LED modulation method which enabled measurement of photocurrent in the presence of large faradaic currents from the sacrificial reactant (hydroquinone) at a variety of applied potentials.[1] The photocurrents generated from a monolayer composed of RCs and MCH resulted in consistent photocurrent currents. which enabled modeling of the photocurrent generation using the Marcus-Hush-Chidsey theory to extract a reorganization energy for this process. Multilayers of adsorbed RCs were distinctly different and revealed that the local environment in which the RCs are embedded significantly influenced photocurrent generation. [1] Jun, D.; Beatty, J. T.; Bizzotto, D. Highly Sensitive Method to Isolate Photocurrent Signals From Large Background Redox Currents on Protein‐Modified Electrodes. ChemElectroChem 2019, 6 (11), 2870–2875.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".